方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 贝叶斯双因素方差分析× | 贝叶斯 t 检验× | |
|---|---|---|
| 领域≠ | 统计学 | 贝叶斯 |
| 方法族≠ | Hypothesis test | Bayesian methods |
| 起源年份≠ | 1961 (foundations); 2012 (default Bayes factor formulation) | 2009 |
| 提出者≠ | Harold Jeffreys (foundational); modern default-prior form by Jeffrey N. Rouder et al. | Rouder, Speckman, Sun, Morey & Iverson |
| 类型 | Bayesian hypothesis test | Bayesian hypothesis test |
| 开创性文献≠ | Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56(5), 356–374. DOI ↗ | Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D. & Iverson, G. (2009). Bayesian t Tests for Accepting and Rejecting the Null Hypothesis. Psychonomic Bulletin & Review, 16(2), 225–237. DOI ↗ |
| 别名≠ | Bayesian factorial ANOVA, Bayes factor two-way ANOVA, Bayesian 2×k ANOVA, Bayesian two-factor ANOVA | bayesian two-sample t-test, bayes factor t-test, Bayesçi t-Testi |
| 相关≠ | 4 | 5 |
| 摘要≠ | Bayesian two-way ANOVA extends the classical two-way analysis of variance by replacing p-values with Bayes factors and posterior distributions. It quantifies evidence for or against main effects and their interaction using prior-weighted model comparison, yielding conclusions that are directly interpretable in probabilistic terms rather than relying on a fixed significance threshold. | The Bayesian t-test, formalised by Rouder and colleagues in 2009, is a two-group comparison method that works within a Bayesian framework. Instead of a p-value, it produces a Bayes Factor (BF₁₀) that quantifies the evidence the data provide for the alternative hypothesis relative to the null, and it reports the full posterior distribution of the standardised effect size δ with a highest-density interval. |
| ScholarGate数据集 ↗ |
|
|